Materials Map

Discover the materials research landscape. Find experts, partners, networks.

  • About
  • Privacy Policy
  • Legal Notice
  • Contact

The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

×

Materials Map under construction

The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

To Graph

1.080 Topics available

To Map

977 Locations available

693.932 PEOPLE
693.932 People People

693.932 People

Show results for 693.932 people that are selected by your search filters.

←

Page 1 of 27758

→
←

Page 1 of 0

→
PeopleLocationsStatistics
Naji, M.
  • 2
  • 13
  • 3
  • 2025
Motta, Antonella
  • 8
  • 52
  • 159
  • 2025
Aletan, Dirar
  • 1
  • 1
  • 0
  • 2025
Mohamed, Tarek
  • 1
  • 7
  • 2
  • 2025
Ertürk, Emre
  • 2
  • 3
  • 0
  • 2025
Taccardi, Nicola
  • 9
  • 81
  • 75
  • 2025
Kononenko, Denys
  • 1
  • 8
  • 2
  • 2025
Petrov, R. H.Madrid
  • 46
  • 125
  • 1k
  • 2025
Alshaaer, MazenBrussels
  • 17
  • 31
  • 172
  • 2025
Bih, L.
  • 15
  • 44
  • 145
  • 2025
Casati, R.
  • 31
  • 86
  • 661
  • 2025
Muller, Hermance
  • 1
  • 11
  • 0
  • 2025
Kočí, JanPrague
  • 28
  • 34
  • 209
  • 2025
Šuljagić, Marija
  • 10
  • 33
  • 43
  • 2025
Kalteremidou, Kalliopi-ArtemiBrussels
  • 14
  • 22
  • 158
  • 2025
Azam, Siraj
  • 1
  • 3
  • 2
  • 2025
Ospanova, Alyiya
  • 1
  • 6
  • 0
  • 2025
Blanpain, Bart
  • 568
  • 653
  • 13k
  • 2025
Ali, M. A.
  • 7
  • 75
  • 187
  • 2025
Popa, V.
  • 5
  • 12
  • 45
  • 2025
Rančić, M.
  • 2
  • 13
  • 0
  • 2025
Ollier, Nadège
  • 28
  • 75
  • 239
  • 2025
Azevedo, Nuno Monteiro
  • 4
  • 8
  • 25
  • 2025
Landes, Michael
  • 1
  • 9
  • 2
  • 2025
Rignanese, Gian-Marco
  • 15
  • 98
  • 805
  • 2025

Bills, Paul

  • Google
  • 14
  • 28
  • 35

University of Huddersfield

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (14/14 displayed)

  • 2024Trueness of vat-photopolymerization printing technology of interim fixed partial denture with different building orientation1citations
  • 2021Comparison and appraisal of techniques for the determination of material loss from tapered orthopaedic surfaces3citations
  • 2020Challenges in Inspecting Internal Features for SLM Additive Manufactured Build Artifacts1citations
  • 2020The Detection of Unfused Powder in EBM and SLM Additive Manufactured Components4citations
  • 2020Development of an Additive Manufactured Artifact to Characterize Unfused Powder Using Computed Tomography6citations
  • 2019The challenges in edge detection and porosity analysis for dissimilar materials additive manufactured componentscitations
  • 2018Optimization of surface determination strategies to enhance detection of unfused powder in metal additive manufactured componentscitations
  • 2018Development of an AM artefact to characterize unfused powder using computer tomographycitations
  • 2018Characterisation of powder-filled defects in additive manufactured surfaces using X-ray CTcitations
  • 2017The influence of hydroalcoholic media on the performance of Grewia polysaccharide in sustained release tablets15citations
  • 2017Results from an interlaboratory comparison of areal surface texture parameter extraction from X-ray computed tomography of additively manufactured partscitations
  • 2017Method for characterizing defects/porosity in additive manufactured components using computer tomographycitations
  • 2016Method for Characterization of Material Loss from Modular Head-Stem Taper Surfaces of Hip Replacement Devices5citations
  • 2006The use of CMM techniques to assess the wear of total knee replacementscitations

Places of action

Chart of shared publication
Kusumasari, Citra
1 / 2 shared
Mahrous, Aliaa
1 / 1 shared
Blunt, Liam
12 / 23 shared
Radwan, Mohamed
2 / 3 shared
Abdou, Ahmed
1 / 4 shared
Tawfik, Ahmed
9 / 11 shared
Addinall, Katie
1 / 2 shared
Dransfield, Karl
1 / 1 shared
Beerlink, Andre
1 / 2 shared
Racasan, Radu
10 / 11 shared
Bacheva, Desi
2 / 2 shared
Attia, Mazen Ahmed
1 / 1 shared
Conway, Barbara
1 / 8 shared
Walton, Karl
1 / 5 shared
Adebisi, Dr Adeola O.
1 / 2 shared
Asare-Addo, Kofi
1 / 13 shared
Dawson, C.
1 / 1 shared
Mahdi, Mohammed
1 / 1 shared
Nep, Elijah I.
1 / 1 shared
Smith, Alan
1 / 12 shared
Leach, Richard K.
1 / 12 shared
Thompson, Adam
1 / 15 shared
Senin, Nicola
1 / 11 shared
Townsend, Andrew
1 / 5 shared
Skinner, John A.
1 / 3 shared
Hart, Alister
1 / 6 shared
Pantelis, Costas
1 / 1 shared
Hardaker, Cath
1 / 1 shared
Chart of publication period
2024
2021
2020
2019
2018
2017
2016
2006

Co-Authors (by relevance)

  • Kusumasari, Citra
  • Mahrous, Aliaa
  • Blunt, Liam
  • Radwan, Mohamed
  • Abdou, Ahmed
  • Tawfik, Ahmed
  • Addinall, Katie
  • Dransfield, Karl
  • Beerlink, Andre
  • Racasan, Radu
  • Bacheva, Desi
  • Attia, Mazen Ahmed
  • Conway, Barbara
  • Walton, Karl
  • Adebisi, Dr Adeola O.
  • Asare-Addo, Kofi
  • Dawson, C.
  • Mahdi, Mohammed
  • Nep, Elijah I.
  • Smith, Alan
  • Leach, Richard K.
  • Thompson, Adam
  • Senin, Nicola
  • Townsend, Andrew
  • Skinner, John A.
  • Hart, Alister
  • Pantelis, Costas
  • Hardaker, Cath
OrganizationsLocationPeople

document

Development of an AM artefact to characterize unfused powder using computer tomography

  • Blunt, Liam
  • Racasan, Radu
  • Bills, Paul
  • Tawfik, Ahmed
Abstract

Additive manufacturing (AM) is recognized as a core technology for producing high value components. Producing complex and individually modified components as well as prototypes gives additive manufacturing a substantial advantage over conventional subtractive machining. One of the current barriers for most industries in implementing AM is the lack of build repeatability and a deficit in quality assurance standards. The mechanical properties of the components depend critically on the density achieved therefore defect/porosity analysis must be carried out to verify the components’ integrity and viability.Detecting unfused powder in AM parts using computer tomography is a challenge because the detection relies on differences in density. <br/>This paper presents an optimized methodology for differentiating between unfused powder and voids in additive manufactured components using computer tomography. Detecting the unfused powder requires detecting the cavities between particles, from previous work it was found that detecting unfused powder requires voxel size as small as 4µm3. For most applications scanning with small voxel size is not reasonable; due to part size, long scan time and data analysis. In this investigation different voxel size used to compare the time for scan and data analysis showing the impact of voxel size on micro defects detection. The powder used was Ti6AL4V with a grain size of 45-100µm, typically employed by Arcam electron beam melting (EBM) machines. The artefact consisted of a 6mm round bar with designed internal features ranging from 50µm to 1400µm that contain a mixture of voids and unfused powder. The diameter and depth of defects were characterised using focus variation microscope then scanned with A Nikon XTH 225 industrial CT was used to measure the artefacts and characterise the internal features for defects/pores. <br/>To reduce the number of process variables, the measurement parameters, such as filament current, acceleration voltage and X-ray filtering material and thickness are kept constant. VgStudio Max 3.0(Volume Graphics, Germany) software package was used for data processing, surface determination and defects/ porosity analysis. The main focus of the study is exploring the optimum methods to enhance the detection capability of pores/defects whilst at the same time minimising the time taken for scan, data analysis and effects of noise on the analysis.<br/>

Topics
  • density
  • impedance spectroscopy
  • pore
  • surface
  • grain
  • grain size
  • tomography
  • void
  • porosity
  • electron beam melting